The present invention relates to an image processing device, an endoscope system, an image processing method, and the like.
There is a need for a technique that extracts a feature quantity from time-series images to implement scene classification, and calculates (determines) the scene change position. The scene classification process may be designed to detect a change in scene when a change from one state to another state has occurred. For example, such a scene classification process is used when the object (e.g., internal organ) change position is estimated from images captured using a capsule endoscope. For example, JP-A-2004-321603 and JP-A-2007-175432 disclose such a method.
The method disclosed in JP-A-2004-321603 calculates a red level and a blue level of an image, performs a low-pass filtering process in the time-axis direction to generate a graph of the red level and a graph of the blue level, detects a color change edge from each graph, and automatically determines the internal organ range from the temporal position of the color change edge.
The method disclosed in JP-A-2007-175432 performs a smoothing process using a filter having a specific size on a feature quantity in the time-axis direction to detect a change from the stomach to the small intestine. For example, a filter having a size of 20 (i.e., 20 images in the time-axis direction) is used as the filter having a specific size.
For example, a Gaussian filter represented by the following expression (1) is used as the low-pass filter in the time-axis direction.
                              1                                                    2                ⁢                π                                      ⁢            σ                          ⁢                  exp          (                      -                                          x                2                                            2                ⁢                                  σ                  2                                                              )                                    (        1        )            